Calculation of Host–Guest Binding Affinities Using a Quantum-Mechanical Energy Model

The prediction of protein–ligand binding affinities is of central interest in computer-aided drug discovery, but it is still difficult to achieve a high degree of accuracy. Recent studies suggesting that available force fields may be a key source of error motivate the present study, which reports th...

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Bibliographic Details
Published inJournal of chemical theory and computation Vol. 8; no. 6; pp. 2023 - 2033
Main Authors Muddana, Hari S, Gilson, Michael K
Format Journal Article
LanguageEnglish
Published United States American Chemical Society 12.06.2012
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Summary:The prediction of protein–ligand binding affinities is of central interest in computer-aided drug discovery, but it is still difficult to achieve a high degree of accuracy. Recent studies suggesting that available force fields may be a key source of error motivate the present study, which reports the first mining minima (M2) binding affinity calculations based on a quantum mechanical energy model, rather than an empirical force field. We apply a semiempirical quantum-mechanical energy function, PM6-DH+, coupled with the COSMO solvation model, to 29 host–guest systems with a wide range of measured binding affinities. After correction for a systematic error, which appears to derive from the treatment of polar solvation, the computed absolute binding affinities agree well with experimental measurements, with a mean error of 1.6 kcal/mol and a correlation coefficient of 0.91. These calculations also delineate the contributions of various energy components, including solute energy, configurational entropy, and solvation free energy, to the binding free energies of these host–guest complexes. Comparison with our previous calculations, which used empirical force fields, point to significant differences in both the energetic and entropic components of the binding free energy. The present study demonstrates a successful combination of a quantum mechanical Hamiltonian with the M2 affinity method.
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ISSN:1549-9618
1549-9626
DOI:10.1021/ct3002738